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Record W4388001887 · doi:10.4000/lidil.11884

Claudine Moïse et Martine Pons-Desoutter, Ce que les mathématiques font aux filles

2023· article· fr· W4388001887 on OpenAlexaff
Véronique Durocher

Bibliographic record

VenueLidil · 2023
Typearticle
Languagefr
FieldSocial Sciences
TopicSocial Policies and Family
Canadian institutionsUniversité du Québec à Trois-Rivières
Fundersnot available
KeywordsHumanitiesArt

Abstract

fetched live from OpenAlex

Les mathématiques traversent le parcours scolaire dès le primaire. Discipline « reine », sa réussite au collège et au lycée est l’une des clés qui permettent d’accéder aux études supérieures en STEM (sciences, technologie, ingénierie et mathématiques), puis à des métiers scientifiques ou liés au numérique. Or, tous et toutes n’ont pas la même expérience avec cette discipline. Elle fait parfois naitre des émotions telles que de la détestation, voire de la haine chez certain·e·s apprenant·e·s....

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.022
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.011
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.004
Scholarly communication0.0050.005
Open science0.0010.002
Research integrity0.0030.006
Insufficient payload (model declined to judge)0.0220.007

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.052
GPT teacher head0.346
Teacher spread0.294 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

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